KSHITIJ JAIN

Engineered and deployed a machine learning and deep learning pipeline, achieving high precision in detecting cyberattacks from network traffic and securing cloud infrastructure.

Developed an employee attrition predictive model with 85%+ accuracy by leveraging EDA, transforming raw HR data into actionable insights for strategic HR retention.

Modeled decades of climate data using time-series analysis to predict temperature trends and identify environmental correlations, informing data-driven climate policy recommendations.

Developed and deployed a Food Delivery Time Prediction model utilizing Random Forest Regression, accurately estimating delivery times based on dynamic factors like vehicle, weather, and traffic data.

Created and deployed an interactive Streamlit web application on Render, providing end-users with real-time delivery predictions and enhancing user experience.

Analyzed customer churn data for over 5,000 customers using Python, identifying critical trends that contributed to a 20% reduction in churn risk.

Utilized advanced data analysis and visualization techniques in Python to effectively interpret complex patterns and communicate key findings.

Engineered and optimized a Random Forest model, achieving 85% accuracy in predicting customer churn and providing a robust solution for retention strategies.

Orchestrated the first 14-hour hackathon in six years, successfully hosting 30 teams and 180 participants and significantly enhancing institutional engagement.

Formed and led a dedicated committee responsible for curating a diverse portfolio of problem statements across multiple domains, ensuring broad participant appeal and relevance.

Managed the successful organization of an 8-hour hackathon, engaging 50 teams and 300 participants, and ensuring seamless event execution.

Directed comprehensive event logistics, marketing campaigns, and team coordination efforts, resulting in a highly organized and positive experience for all participants.